Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data

Hesam Khazraj; Filipe Miguel Faria da Silva; Claus Leth Bak

doi:10.1109/EEEIC.2017.7977482

Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data

Hesam Khazraj, Filipe Miguel Faria da Silva, Claus Leth Bak

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

4 Citations (Scopus)

Abstract

Detection and analysis of bad data is one of the most important sector of static state estimation. This paper focuses on the comparison between a novel method for multi bad data detection and identification in PMU-based state estimation, namely post-processing PMU-based method for state estimation and the conventional PMU-based state estimation. To accomplish this object, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the second level of state estimation. The proposed algorithm of phasor measurements utilization in state estimation can prove that post-processing algorithm can detect and identify multi bad data in critical measurements, which it is not detectable by conventional methods. To validate simulations, IEEE 30 bus is implemented in PowerFactory and Matlab is used to solve proposed state estimation using post-processing of PMUs. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analysis of bad data are available by result of largest normalized residual test.

Original language	English
Title of host publication	Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Number of pages	6
Place of Publication	Milan, Italy
Publisher	IEEE Press
Publication date	Jun 2017
ISBN (Print)	978-1-5386-3917-7
DOIs	https://doi.org/10.1109/EEEIC.2017.7977482
Publication status	Published - Jun 2017
Event	2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) - Milano, Italy Duration: 6 Jun 2017 → 9 Jun 2017

Conference

Conference	2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)
Country/Territory	Italy
City	Milano
Period	06/06/2017 → 09/06/2017

Keywords

Bad Data
Critical Measurement
Largest Normalized Residual
Phase Measurement unit
State Estimation

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10.1109/EEEIC.2017.7977482

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Khazraj, H., Silva, F. M. F. D., & Bak, C. L. (2017). Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data. In Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) IEEE Press. https://doi.org/10.1109/EEEIC.2017.7977482

Khazraj, Hesam ; Silva, Filipe Miguel Faria da ; Bak, Claus Leth. / Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data. Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Milan, Italy : IEEE Press, 2017.

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title = "Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data",

abstract = "Detection and analysis of bad data is one of the most important sector of static state estimation. This paper focuses on the comparison between a novel method for multi bad data detection and identification in PMU-based state estimation, namely post-processing PMU-based method for state estimation and the conventional PMU-based state estimation. To accomplish this object, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the second level of state estimation. The proposed algorithm of phasor measurements utilization in state estimation can prove that post-processing algorithm can detect and identify multi bad data in critical measurements, which it is not detectable by conventional methods. To validate simulations, IEEE 30 bus is implemented in PowerFactory and Matlab is used to solve proposed state estimation using post-processing of PMUs. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analysis of bad data are available by result of largest normalized residual test.",

keywords = "Bad Data, Critical Measurement, Largest Normalized Residual, Phase Measurement unit, State Estimation",

author = "Hesam Khazraj and Silva, {Filipe Miguel Faria da} and Bak, {Claus Leth}",

year = "2017",

month = jun,

doi = "10.1109/EEEIC.2017.7977482",

language = "English",

isbn = "978-1-5386-3917-7",

booktitle = "Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)",

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note = "2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe) ; Conference date: 06-06-2017 Through 09-06-2017",

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Khazraj, H, Silva, FMFD & Bak, CL 2017, Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data. in Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE Press, Milan, Italy, 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Milano, Italy, 06/06/2017. https://doi.org/10.1109/EEEIC.2017.7977482

Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data. / Khazraj, Hesam; Silva, Filipe Miguel Faria da ; Bak, Claus Leth.
Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Milan, Italy: IEEE Press, 2017.

Research output: Contribution to book/anthology/report/conference proceeding › Article in proceeding › Research › peer-review

TY - GEN

T1 - Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data

AU - Khazraj, Hesam

AU - Silva, Filipe Miguel Faria da

AU - Bak, Claus Leth

PY - 2017/6

Y1 - 2017/6

N2 - Detection and analysis of bad data is one of the most important sector of static state estimation. This paper focuses on the comparison between a novel method for multi bad data detection and identification in PMU-based state estimation, namely post-processing PMU-based method for state estimation and the conventional PMU-based state estimation. To accomplish this object, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the second level of state estimation. The proposed algorithm of phasor measurements utilization in state estimation can prove that post-processing algorithm can detect and identify multi bad data in critical measurements, which it is not detectable by conventional methods. To validate simulations, IEEE 30 bus is implemented in PowerFactory and Matlab is used to solve proposed state estimation using post-processing of PMUs. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analysis of bad data are available by result of largest normalized residual test.

AB - Detection and analysis of bad data is one of the most important sector of static state estimation. This paper focuses on the comparison between a novel method for multi bad data detection and identification in PMU-based state estimation, namely post-processing PMU-based method for state estimation and the conventional PMU-based state estimation. To accomplish this object, available approaches in the PMU-based state estimation are overviewed, and their advantages and disadvantages are briefly explained. The largest normalized residual test is used to identify bad data. Then, phasor measurements are added by post-processing step in the second level of state estimation. The proposed algorithm of phasor measurements utilization in state estimation can prove that post-processing algorithm can detect and identify multi bad data in critical measurements, which it is not detectable by conventional methods. To validate simulations, IEEE 30 bus is implemented in PowerFactory and Matlab is used to solve proposed state estimation using post-processing of PMUs. Bad data is generated manually and added in PMU and conventional measurements profile. Finally, the location and analysis of bad data are available by result of largest normalized residual test.

KW - Bad Data

KW - Critical Measurement

KW - Largest Normalized Residual

KW - Phase Measurement unit

KW - State Estimation

U2 - 10.1109/EEEIC.2017.7977482

DO - 10.1109/EEEIC.2017.7977482

M3 - Article in proceeding

SN - 978-1-5386-3917-7

BT - Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

PB - IEEE Press

CY - Milan, Italy

T2 - 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe)

Y2 - 6 June 2017 through 9 June 2017

ER -

Khazraj H, Silva FMFD , Bak CL. Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data. In Proceedings of the 2017 IEEE International Conference on Environment and Electrical Engineering and 2017 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Milan, Italy: IEEE Press. 2017 doi: 10.1109/EEEIC.2017.7977482

Comparison Between Conventional and Post-Processing PMU-Based State Estimation to Deal with Bad Data

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